Increase In Annual Precipitation Research Articles

Spatiotemporal dynamics of blue and green water resources in a mountainous watershed: A case study of the Wujiang River Basin, China

Study regionWujiang River Basin, China. Study focusBlue and green water play key roles in water management and sustainable development in the Wujiang River Basin. It is essential to conduct a comprehensive study on the availability of blue and green water resources due to the uneven distribution of water resources in the basin. In this study, the monthly, seasonal, and interannual variations in blue and green water resources were analyzed during 1985–2014, and the changes in blue and green water resources were predicted for the period 2015–2100 based on the 5 Coupled Model Intercomparison Project Phase 6 (CMIP6). New hydrological insights for the regionFrom 1985–2014, blue water resources were dominant in the Wujiang River basin, accounting for 53.6% of the total water resources. Blue water resources exhibited an increasing trend, while green water resources exhibited a decreasing trend. Precipitation exhibited a much more significant impact on blue water resources than on green water resources. The spatial distribution of blue and green water resources in the basin is uneven, where the blue water resource with an annual average of 629.5 mm, indicating an increase followed by a decreasing trend from upstream to downstream. The green water resources had an annual average of 544.7 mm, with a decrease followed by an increasing trend from upstream to downstream. Delta and multi-model ensemble (MME) can effectively reduce the uncertainties associated with CMIP6 model output. Annual precipitation and mean annual temperature increase from 2015 to 2100 in SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5. Compared to the baseline period, blue water resources show the highest growth in the recent (2015–2040) and intermediate (2041–2070) periods in SSP1–2.6, i.e., by 4.9% and 13.7%, respectively. In the final period (2071–2100), blue water resources exhibit the highest growth in SSP5–8.5, i.e., by 21.5%. The future projections indicated that the uneven spatial distribution of blue water resources in the basin will persist. This study improves our understanding of the blue and green water resources in the Wujiang River Basin under climate change scenarios and can provide valuable insights for integrated water resources management in the Wujiang River Basin.

Water quality impacts of climate change, land use, and population growth in the Chesapeake Bay watershed

AbstractThe 2010 Chesapeake Bay Total Maximum Daily Load was established for the water quality and ecological restoration of the Chesapeake Bay. In 2017, the latest science, data, and modeling tools were used to develop revised Watershed Implementation Plans (WIPs). In this article, we examine the vulnerability of the Chesapeake Bay watershed to the combined pressures of climate change and growth in population, agricultural intensity, and economic activity for the 60‐year period 1995–2055. The results will be used to revise WIPs, as needed, to account for expected increases in loads. Assessing changes relative to 1995 for the years 2025, 2035, 2045, and 2055, mean annual precipitation increases of 3.11%, 4.21%, 5.34%, and 6.91%, respectively, air temperature increases of 1.12, 1.45, 1.84, and 2.12°C, respectively, and potential evapotranspiration increases of 3.36%, 4.43%, 5.54%, and 6.35%, respectively, are projected. Population in the watershed is expected to grow by 3.5 million between 2025 and 2055. Watershed model results show incremental increases in streamflow (2.3%–6.2%), nitrogen (2.6%–10.8%), phosphorus (4.5%–26.7%), and sediment (3.8%–18.8%) loads to the tidal Bay due to climate change. Growth in population, agricultural intensity, development, and economic activity resulted in relatively smaller increases in loads compared to climate change.

Simulating the hydrological impacts of intensive soil and water conservation measures in the Yellow River basin using a distributed physically-based model

Intensive Soil and Water Conservation (SWC) has been conducted in the Yellow River basin (YRB) since the 1950s, which has greatly altered the eco-hydrological processes and particularly led to the runoff reduction. However, previous hydrological models performed in the YRB rarely simulated the SWC explicitly to quantify its spatiotemporal impacts. This study developed a SWC parameterization scheme based on the distributed physically-based model named Geomorphology-Based Ecohydrological Model (GBEHM). The hillslope SWC (HSWC) was parameterized as an additional surface storage capacity and simulated together with hillslope hydrological processes. The check dams along the river networks (i.e., river-networks SWC, RSWC) were parameterized as reservoirs and simulated together with the flow routing. The enhanced model (GBEHM-SWC) was first calibrated and validated using natural streamflow and remote sensing-based evapotranspiration. Then it was applied to analyze the hydrological changes from 1982 to 2019 in the YRB. Our simulation showed that, compared with the first period (1982–2000), the climatic factors (especially an increase of annual precipitation by 27.3 mm) would cause an increase of annual natural runoff by 2.9 mm (2.17 billion m3) in the second period (2001–2019). But in fact, the observed annual natural runoff decreased by 4.3 mm in the second period, which was caused by the reduction effects of the HSWC and RSWC by 3.8 and 3.7 mm (2.84 and 2.74 billion m3), respectively. Regarding the spatial distribution, the simulated natural runoff increased above Lanzhou and decreased on the Loess Plateau. The SWC impacts showed high spatial heterogeneity over the YRB, which offered useful information to evaluate the SWC measures.

Assessing hydrological sensitivity to future climate change over the Canadian southern boreal forest

This study develops a physically based hydrological process model using the Cold Region Hydrological Modelling (CRHM) platform to simulate the water budget storages and fluxes over the Canadian southern boreal forest (SBF). Evaluation of the CRHM-based model in a well-gauged SBF basin, White Gull Creek (WGC), Saskatchewan, Canada, indicated quite good performance in reproducing historical observations of streamflow, snow water equivalent (SWE), evapotranspiration (ET) and soil moisture without parameter calibration from streamflow. The entire SBF was then evenly divided into 2243 virtual basins, each of which was structured and parameterized with the same land cover, soil and hydrological parameters as the WGC basin, but with local latitude and topography in order to examine the sensitivity of governing hydrological processes to future climate variability and perturbation. Hydrological sensitivity in the virtual basins was assessed by examining the differences between hydrological simulations driven by 4-km gridded convection-permitting Weather Research and Forecasting (WRF) outputs in the current period (ctrl, 2001–2013) and a Pseudo Global Warming period (pgw, 2087–2099). The WRF simulation in the pgw period was forced by a perturbation of the same boundary conditions from ERA reanalysis data as for the ctrl period, and the perturbation was based on the ensemble-mean of projected changes from the CMIP5 RCP 8.5 emission scenario. Results showed that temperature would increase by 4.5℃ to 7℃ over the SBF but increases in annual precipitation of 15–24% would more than compensate for the effects of warming on runoff generation and result in greater streamflow volumes. Annual streamflow volumes would increase by 64 mm (35%) and 95 mm (16%) in the west and east, and by 48 mm (17%) in the central SBF. Annual snowfall and maximum SWE would decrease by 89–109 mm (∼29%) in the east, 3–8 mm (∼6%) in the west, and 31–50 mm (∼20%) in the central SBF. Annual mean soil moisture storage would decrease by 54–56 mm (27%) in the west and central, and by only 37 mm (14%) in the east SBF. Decreases in soil moisture would be caused by reduced soil freezing and enhanced thawing under future warming which would increase soil water loss from ET, subsurface runoff and percolation into groundwater storage. The larger sensitivity of streamflow and snow processes in the east SBF is partly due to the wetter climate and the larger increase in annual precipitation, the later also buffered the sensitivity of soil moisture to warming. These results show that the SBF would switch to a higher water yield region, dominated by rainfall-runoff fed streamflow over a longer snow-free season, and provide first-order guidance for sustainable water management of the SBF in the future.

The effect of experimental warming on fine root functional traits of woody plants: Data synthesis

Fine root traits are critical to plant nutrition and water uptake, and soil nutrient cycling. The impacts of climate warming on woody plants are predicted to be severe, but the effects on the fine root traits of woody plants remain unclear. To evaluate the effects of warming on fine-root traits of woody plants, we synthesized 431 paired observations of 13 traits from 78 studies. The result showed that warming increased the fine root nitrogen (N) concentration, root mortality, and root respiration, but decreased fine root phosphorus (P) concentration, root C:N and root nonstructural carbohydrates (NSC) concentration. However, warming had no significant effect on fine root biomass, root production and morphological traits. Warming effects on fine root biomass and root diameter decreased with warming magnitude, while root P concentration increased. Moreover, with increasing warming duration, the effect size of specific root length (SRL), root length, root C:N and root NSC increased. The effects size of root biomass, root diameter, root length and root C:N decreased with mean annual temperature (MAT) and mean annual precipitation (MAP) increase. However, the effect size of root N concentration increased with higher MAT and MAP. Furthermore, warming increased the fine root biomass of ectomycorrhiza (ECM) plants, but decreased that of plants associated with arbuscular mycorrhizal (AM) fungi. These results indicate that the effect of warming on fine root traits of woody plants was not only modulated by warming duration and magnitude, but also MAT and MAP. Our findings highlight the differential warming responses to fine root traits of woody plants, which have strong implications for shrubs and tree-dominated ecosystems soil nutrients cycling and carbon stocks.

Precipitation-based climate change hotspots across India through a Multi-model assessment from CMIP6

This study presents an analysis to identify precipitation-based climate change hotspots and key-vulnerable cities using multi-model, multi-scenario, high-resolution (0.25°×0.25°), bias-corrected precipitation dataset across India from 14 state-of-the-art General Circulation Models (GCMs), participating in Coupled Model Intercomparison Project version 6 (CMIP6). Preliminary analysis indicates an overall wetter future across India with 290 ± 150 mm to 530 ± 260 mm increase in mean annual precipitation towards end of this century under various climate change scenarios. Apart from the mean precipitation, the extremes are also found to be increasing by alarmingly higher rates. However, the spatio-temporal variations of such increments are notably diverse over different seasons in a year and across different Homogeneous Precipitation Zones (HPZs) in the country. Therefore, a new and more inclusive index, named as Precipitation-based Hotspot Index (PHI), is developed to identify the ‘precipitation-based hotspots’, i.e. the places with most pronounced changes in precipitation characteristics. The PHI considers the changes in various aspects of precipitation, such as mean, variability, and characteristics of extremes (magnitude, frequency and intensity). Based on the PHI values in the far-future period (2061–2100) and for the worst climate change scenario, the hotspot regions are identified mostly in the northwest, west-central, west coast, and northeast parts of India. Further, considering two important socio-economic vulnerability factors (population density and human development index) along with PHI, the key-vulnerable tier-I cities are identified across India. The analysis reveals four out of ten tier-I cities will be highly vulnerable towards end of this century. The findings of this analysis (hotspot maps) and the data products (high-resolution, bias-corrected precipitation dataset) are expected to be highly beneficial for impact assessments, hydrologic modelling, and formulating suitable adaptation and mitigation strategies for India over future.

Assessment of impact of climate change on the streamflow of Idamalayar River Basin, Kerala

Abstract This study investigates the impacts of climate change on water availability in the Idamalayar basin, Kerala. Soil and Water Assessment Tool (SWAT), Hydrologic Engineering Centre – Hydrologic Modelling System (HEC-HMS), and bias-corrected climate change data were used to simulate future streamflows. The performances of SWAT and HEC-HMS were assessed using four statistical indices (R2, Nash–Sutcliffe efficiency, percentage bias, and RSR). SWAT slightly outperformed HEC-HMS. The CMIP6 general circulation models (GCMs) were selected using PROMETHEE-2. The variations in climate variables and streamflows were studied for three future periods, i.e., near-future (2031–2040), mid-future (2051–2060), and far-future (2071–2080) under three shared socio-economic pathway (SSP) scenarios (SSP126, SSP245, and SSP585). The projections of GCMs show different patterns in variation of precipitation. Generally, there is a slight increase in annual precipitation. However, there was a notable decline in peak in July. An additional peak was often seen in October. The maximum and minimum temperatures showed a decreasing trend. The average annual streamflow reduction under SSP126 was approximately 25.63, 27.92, and 26.24% in the near, mid, and far future, respectively. Under SSP245, the average decrease was 30.71, 16.06, and 19.06% for the near, mid and far future, respectively. For SSP585, there was 12.73% increase in the far-future period.

Extracellular enzyme activities response to nitrogen addition in the rhizosphere and bulk soil: A global meta-analysis

Plant roots play a crucial role in acquiring available nutrients and regulating microbial decomposition, leading to faster nutrient cycling in the rhizosphere than in bulk soil. With increasing nitrogen (N) loading, rhizosphere processes may become more crucial than bulk soil processes for accurately predicting nutrient cycling process changes. However, it remains unclear how the rhizosphere and bulk soil extracellular enzyme activities (EEAs) respond to N addition on a global scale. Therefore, we used a global meta-analysis to examine the effects of N addition on EEAs involved in carbon (C), N, and phosphorus (P) acquisition in paired rhizosphere and bulk soils, based on 1992 observations from 40 studies. Overall, N addition significantly increased β-xylosidase (BXYL) activity by 17.0% in bulk soil, together with urease (URE) activity in both the rhizosphere (25.3%) and bulk soil (33.6%). In addition, N addition marginally significantly decreased phenol oxidase (PHEO) activity in the rhizosphere (−18.4%), as well as peroxidase (PERO) activity in both the rhizosphere (−12.6%) and bulk soil (−13.6%). The reductions may be caused by fungi: bacteria ratio and Gram+ bacteria: Gram− bacteria ratio (F: B and G+: G−, respectively) reductions. We also found that EEAs (e.g., acid/alkaline phosphatase (AP) and PHEO) did not always have a simple linear relationship with higher N addition rate and duration. Additionally, the responses of β-1,4-N-acetyl-glucosaminnidase (NAG) and PHEO significantly increased with increase in mean annual temperature (MAT), whereas those of microbial biomass carbon (MBC) and microbial biomass nitrogen (MBN) significantly decreased with increase in mean annual precipitation (MAP). Moreover, the responses of PHEO and PERO significantly decreased along altitudinal gradients. Furthermore, we found that the N sensitivity of rhizosphere C-acquisition (BG, PHEO, and PERO) and P-acquisition (AP) enzyme activities was significantly lower than that of bulk soil, but no significant difference was noted in N-acquisition enzyme activities except for the NAG which exhibited marginal significant differences between the rhizosphere and bulk soil. Our results suggest that EEAs in the rhizosphere and bulk soil have different response patterns, and these differences might mainly be caused by soil nutrient availability and microbial attributes. These results deepen our understanding of rhizosphere and bulk soil nutrient cycling processes under increasing N loading. They also provide extensive evidence and a basis for the parameterization of global nutrient cycling models that incorporate rhizosphere responses to climate change.

The impact of global changes in near-term climate forcers on East Africa’s climate

Climate change and air pollution are two interconnected daunting environmental challenges of the twenty-first century. Globally, stringent public health and environmental policies are set to mitigate the emissions of near-term climate forcers (NTCFs) because they double as air pollutants. While the global climate impact of NTCF mitigation has been investigated using coarse resolution climate models, the fine scale regional climate impacts over East Africa are not fully known. This study presents the first 2021–2055 downscaled model results of two future scenarios which both have increasing greenhouse gas emissions but with weak (SSP3-7.0) versus strong (SSP3-7.0_lowNTCF) levels of air quality control. NTCF mitigation is defined here as SSP3-7.0_lowNTCF–SSP3-7.0. The results reveal that NTCF mitigation could cause an increase in annual mean surface temperature ranging from 0.005 to 0.01 °C decade−1 over parts of Kenya, Ethiopia and Somalia. It could also cause an increase in annual mean precipitation ranging from 0.1 to 1 mm month−1 decade−1 over parts of Uganda, Kenya, Tanzania, South Sudan and Ethiopia. Majority of the precipitation increase is projected to occur during the MAM season. On the other hand, Zambia, Malawi and southern Tanzania could also experience a decrease in annual mean precipitation by up to 0.5 mm month−1 decade−1. Majority of this decrease is projected to occur during the DJF season. These findings suggest that pursuing NTCF mitigation alone while ignoring greenhouse gas emissions will cause additional climate change over East Africa. Mitigating both of them concurrently would be a better policy option.

Different hydrological controls causing variable rates of Holocene peat growth in a lowland valley system, north-eastern Netherlands; implications for valley peatland restoration

The Drentsche Aa valley system in the glacial sandy landscape of the north-eastern Netherlands, is one of the many regional drainage systems in the north-western to central European Lowlands. Following deep incision in the Weichselian, ca 7 m of eutrophic peat has accumulated in the lower to middle reaches of the valley system in the Holocene, completely filling the Weichselian incision. We reconstructed the rate of water-level rise controlling peat growth at three locations in the valley system (representing the upper, middle and lower reaches), using 14C peat dates from compaction-free sampling sites on the sloping valley margin where the peat directly overlies the sandy Pleistocene subsurface. The 14C dates enabled the construction of curves showing the water-level evolution at each location. Our results show variable rates of Holocene peat growth in the valley system in response to different drivers of hydrological change: a strong increase in annual precipitation (onset Holocene), a decrease in evapotranspiration (10,000–8000 cal. years BP) and relative sea-level rise (after ~4500 cal. years BP). Because the identified hydrological controls on peat growth are regional, they probably ruled Holocene peat growth in many peat-filled valley systems in the north-western to central European Lowlands. Currently, there is growing attention for these valley systems in the context of European nature restoration efforts and climate change adaptation and mitigation measures. The present study underscores that large-scale hydrological measures outside the valley system are needed for restoration of degraded valley peatlands.

An investigation of the changing patterns of rainfall in the Indravathi subbasin utilizing the Mann-Kendall and Sen’s slope methods

In hydro-meteorological studies, precipitation is an important parameter that is utilized in irrigation system design and management, as well as agricultural planning. Under the effects of climate change, precipitation is predicted to alter, which will have an impact on sustainable development. Using rainfall data for the Indravathi subbasin, Godavari basin, from 1998 to 2016, the spatial variability and temporal trend of precipitation were examined over the region, which has a humid tropical climate. Using non-parametric tests like Mann-Kendall (MK) and Sen’s slope approach, analysis for trend detection was conducted. The test data were loaded into ArcGIS software, which then performed monthly, seasonal, and annual analyses of the spatial and temporal trends of rainfall. According to an analysis of the monthly rainfall trends, February had the largest spatiotemporal declining trend in rainfall, while September had the highest spatiotemporal increasing trend. An analysis of seasonal rainfall data revealed a considerable increase in the tendency for summer rainfall over nearly 80% of the basin. Data on annual precipitation revealed an increase in annual precipitation for the basin’s central eastern sections. The findings of this research may help the decision makers and stakeholders make the most efficient use of hydrological resources by providing insight on the effects of climate change and climatic changes on precipitation patterns in the Indravathi subbasin.

The Use of Historical Data and Global Climate Models to Assess Historical and Future Surface Water and Groundwater Availability in the Trinity River Basin in Texas

This paper describes the results of a study that was done by the USGS to assess recent (2017) water availability, forecast long-term trends in water availability, assess changes in water availability, and forecast future water availability in the Trinity River Basin in Texas. The Trinity River Basin surface water model and Trinity River alluvium aquifer (TRAA) groundwater model were created to evaluate future conditions under different global climate models (GCM). The results of this study show minimal overall changes in water availability for both surface water and groundwater. Trend analyses using historical data (1900–2017) indicated an increase of annual precipitation on the watersheds that drain into the reservoirs in Regional Water Planning Group C. However, the Trinity River Basin surface water model GCM ensemble mean annual precipitation indicates a downward trend, resulting in a downward trend in surface runoff. Additionally, the GCM ensemble mean for the Trinity River Basin surface water model and the TRAA groundwater model both indicate a downward trend in recharge while the TRAA model GCM ensemble mean indicates an upward trend in the amount of groundwater leaving the aquifer to rivers and streams resulting in an upward trend of cumulative storage change.

A comparison of CMIP5 and CMIP6 climate model projections for hydrological impacts in China

Abstract Global climate model (GCM) outputs from Coupled Model Inter-comparison Project Phase 5 (CMIP5) were widely used to investigate climate change impacts last 10 years. It is important to know whether Coupled Model Inter-comparison Project Phase 6 (CMIP6) is more reliable than CMIP5. Number of studies compared GCMs from two CMIPs in simulating climate variables, but they are not in the field of hydrology for large quantities of watersheds. The objective of this study is to compare CMIP5 and CMIP6 climate model projections in projecting hydrological changes between future (2071–2100) and historical (1976–2005) periods and inter-model variability of hydrological impacts for the future period over 343 catchments in China's mainland. The results show that the GCMs in CMIP6 show more increase in daily mean temperature and mean annual precipitation. However, GCMs in CMIP6 and CMIP5 show similar increases in mean and peak streamflow. Moreover, GCMs in CMIP6 show less inter-model variability for streamflow in southern and northeastern China, but more in central China, which is consistent to that for precipitation after bias correction. Overall, this comparison provides the consistency of future change and uncertainty in predicted streamflow with climate simulations, which bring confidence for hydrological impact studies using CMIP6.

Response of runoff to climate change in the area of runoff yield in upstream Shiyang River Basin, Northwest China: A case study of the Xiying River

The objective of this study was to analyze the response of runoff in the area of runoff yield of the upstream Shiyang River basin to climate change and to promote sustainable development of regional water resources and ecological environment. As the biggest tributary of the Shiyang River, Xiying River is the only hydrological station (Jiutiaoling) that has provincial natural river and can achieve long time series monitoring data in the basin. The data obtained from this station is representative of natural conditions because it has little human activites. This study built a regression model through identifying the characteristics of runoff and climate change by using Mann-Kendall nonparametric statistical test, cumulative anomaly, and correlation analysis. The results show that the average annual runoff is 320.6 million m³/a with the coefficient of variation of 0.18 and shows slightly decrease during 1956–2020. It has a significant positive correlation the average annual precipitation (P<0.01). Runoff is sensitive to climate change, and the climate has becoming warm and wet and annual runoff has entering wet period from 2003. Compared to the earlier period (1955–2000), the increases of average annual temperature, precipitation and runoff in recent two decades were 15%, 9.3%, and 7.8%, respectively. Runoff in the Shiyang River is affected by temperature and precipitation among climate factors, and the simulation results of the runoff-climate response model (R = 0.0052P − 0.1589T + 2.373) indicate that higher temperature leads to a weakening of the ecological regulation of surface runoff in the flow-producing area.

Impacts of Climate Change on Natural Runoff in the Yellow River Basin of China during 1961–2020

The change in natural runoff is highly relevant to total river flow dispatch and water resource utilization in the Yellow River Basin (YRB). Based on the annual mean temperature and total precipitation records from 70 meteorological stations from 1961–2020, the impact of climate change on the natural runoff of the YRB is investigated using the Mann-Kendall (M-K) test and Bivariate Wavelet analysis methods. Results show that the annual mean temperature over the YRB increased by 0.33 °C decade−1 during 1961–2020, with a warming rate of more than 0.40 °C decade−1 observed in its northern part. The annual total precipitation increases by 10–20 mm decade−1 in the northwest YRB, while it decreases by 20–30 mm decade−1 in the southeast YRB. The result of the M-K test shows abrupt variations in temperature and natural runoff, especially in the 1980s and 1990s. The decrease in natural runoff is closely tied to the increase (decrease) in temperature (precipitation), especially for the period 1993–2020. The bivariate wavelet coherence analysis further suggests that the decrease in the natural runoff, which has persisted over the past 60 years, is primarily driven by precipitation reduction rather than regional warming. In the stage of rapid warming, the inter-decadal influence of precipitation on natural runoff gradually changes to the influence of inter-annual fluctuation. The finding contributes to providing an important scientific basis for evaluating the optimal allocation of water resources in arid and semi-arid areas against the background of climate change.

Historic climate change trends and impacts on crop yields in key agricultural areas of the prairie provinces in Canada: a literature review

The objective of this literature review was to compile research findings on climate change and its impacts on crop production in Prairie Provinces of Canada. Our search strategy included finding primary literature articles from various databases. Seven articles reported increases in average and minimum air temperature over time in the Prairie Provinces of Canada. Increases in maximum air temperature were smaller than that for minimum air temperature. Growing degree days and corn heat units also increased over time, which has allowed for potential expansion of corn growth northwards. While overall increases in average annual precipitation and growing season precipitation have occurred in Canada between 1900 and 2021, western Canada showed increases in some regions but decreases in others. Off-season precipitation and snow cover duration in Canada have decreased since 1950. The number of frost-free days has increased across Canada, on the Prairies and southern Saskatchewan since 1900. Annual snowfall has decreased since 1950 and across Canada the annual maximum snow depth has also decreased. Overall, studies focusing on the Prairie Provinces in Canada have shown accelerated changes in several climate parameters over time, affecting cropping areas and crop yields.

Evaluation and projection of precipitation extremes under 1.5°C and 2.0°C GWLs over China using bias-corrected CMIP6 models

China is facing an increasing challenge from severe precipitation-related extremes with accelerating global warming. In this study, using a bias-corrected CMIP6 ensemble, future responses of precipitation extreme indices at 1.5°C and 2.0°C global warming levels (GWLs) under the SSP245, SSP370 and SSP585 scenarios are investigated. Despite different change magnitudes, extreme precipitation events will be more frequent and more intense over China as a whole under higher emissions and GWLs. The increase in annual total precipitation could attribute to a sharp increase in the intensity and days of very heavy precipitation in future global warming scenarios. Limiting global warming to 1.5°C and low emission pathways (i.e., SSP245) instead of 2°C and high emission pathways (i.e., SSP585) would have substantial benefits for China in terms of reducing occurrences of extreme precipitation events.

Climate Change and Production of Cereal Crops in East Africa: Role of Temperature, Precipitation, Ecological and Carbon Footprint

This study was conducted to examine the impact of changes in annual mean temperature, annual mean precipitation, carbon footprint, ecological footprint, and area harvested on cereal crop production in East Africa. The study was conducted in a panel cointegration framework using annual time series from 1980 to 2018 for five East African countries i.e., Ethiopia, Kenya, Rwanda, Tanzania, and Uganda. Unit root tests were performed using LLC, IPS, ADF-Fisher, and PP-Fisher tests, while panel co-integration tests were performed using Pedroni residual, Kao residual, and Johansen Fisher panel co-integration tests. Long-run coefficients were estimated using the Pooled Mean Group/Autoregressive Distributed Lag, Panel Fully-modified OLS, and Panel Dynamic OLS models. Empirical findings from the three models revealed that increases in annual mean temperature have adverse effects on cereal crop production, while increases in annual mean precipitation, carbon footprint, ecological footprint, and area harvested have positive effects on cereal crop production in East Africa. Based on these findings, it can be suggested that prioritization of climate change adaptation strategies in the region such as the development of drought and heat-resistant crop varieties, changing in planting dates, and investment in irrigation technologies to boost cereal crops productivity could play a role in minimizing the adverse effects of changes in climate factors.

Future Changes in Climate and Hydroclimate Extremes in East Africa

AbstractClimate change is affecting the agriculture, water, and energy sectors in East Africa and the impact is projected to increase in the future. To allow adaptation and mitigation of the impacts, we assessed the changes in climate and their impacts on hydrology and hydrological extremes in East Africa. We used outputs from seven CMIP‐6 Global Climate Models (GCMs) and 1981–2010 is used as a reference period. The output from GCMs are statistically downscaled using the Bias Correction‐Constructed Analogs with Quantile mapping reordering method to drive a high‐resolution hydrological model. The Variable Infiltration Capacity and vector‐based routing models are used to simulate runoff and streamflow across 68,300 river reaches in East Africa. The results show an increase in annual precipitation (up to 35%) in Ethiopia, Uganda, and Kenya and a decrease (up to 4.5%) in Southern Tanzania in the 2050s (2041–2070) and 2080s (2071–2100). During the long rainy season (March–May), precipitation is projected to be higher (up to 43%) than the reference period in Southern Ethiopia, Kenya, and Uganda but lower (up to −20%) in Tanzania. Large parts of Kenya, Uganda, Tanzania, and Southern Ethiopia show an increase in precipitation (up to 38%) during the short rainy season (October–December). Temperature and evapotranspiration will continue to increase in the future. Further, annual and seasonal streamflow and hydrological extremes (droughts and floods) are projected to increase in large parts of the region throughout the 21st century calling for site‐specific adaptation.

Projected changes in precipitation characteristics over the Drakensberg Mountain Range

AbstractThis study examines the potential impacts of climate change on the characteristics of precipitation over the Drakensberg Mountain Range (DMR) at different global warming levels (GWLs: 1.5, 2.0, 2.5 and 3.0°C) under the Representative Concentration Pathway 8.5 (RCP8.5) scenario, using dynamical and statistical downscaled datasets. The dynamical datasets consist of 19 multi‐model simulations datasets from the Coordinated Regional Climate Downscaling Experiment (CORDEX), whereas the statistical downscaled datasets comprise 19 multi‐model simulations from the National Aeronautics and Space Administration (NASA) Earth Exchange (NEX) Global Daily Downscaled Projections (NEX‐GDDP, hereafter NEX). The capacity of the CORDEX and NEX datasets to represent past characteristics of extreme precipitation over the DMR was evaluated against eight observation datasets. The precipitation characteristics were represented by eight precipitation indices. Both CORDEX and NEX realistically capture the characteristics of extreme precipitation over the Drakensberg and, in most cases, their biases lie within the observation uncertainty. However, NEX performs better than CORDEX in reproducing most of the precipitation characteristics, except in simulating the threshold of extreme rainfall. The ensemble means of CORDEX and NEX agree on a future increase in the intensity of normal precipitation, in the frequency and intensity of extreme precipitation, as well as an increase in widespread extreme events, with a decrease in the number of precipitation days and continuous wet days. However, they disagree on the projected changes of annual precipitation, for which CORDEX projects an increase over most parts of the DMR, whereas NEX indicates a decrease. The self‐organizing‐map analysis, which reveals diversity in the projection patterns hidden in the ensemble means, shows the most probable combinations of projected changes in the annual precipitation and extreme precipitation events (in terms of intensity and frequency): (a) increase in both annual precipitation and extreme precipitation events; (b) decrease in both annual precipitation and extreme precipitation events; (c) decrease in annual precipitation but increase in extreme precipitation events. The results of this study can thus provide a basis for developing climate change adaptation and mitigating strategies over the DMR.